Multimodal Deep Learning for Lymph Node Metastasis Prediction and Physician Performance Assessment in T1 Gastric Cancer
Development and Validation of a Multimodal Artificial Intelligence Model for Predicting Lymph Node Metastasis in T1 Gastric Cancer and Its Impact on Physician Diagnostic Performance
Qun Zhao
300 participants
Jan 1, 2025
OBSERVATIONAL
Conditions
Summary
This study aims to develop and validate an artificial intelligence (AI) model that integrates clinical, pathological, and imaging data to predict the presence of lymph node metastasis (LNM) in patients with T1-stage gastric cancer. The study will also compare the diagnostic performance of physicians with and without AI assistance, including clinicians with varying levels of experience. The goal is to improve early decision-making and support more personalized treatment strategies for patients with early gastric cancer.
Eligibility
Plain Language Summary
Simplified for easier understanding
This summary was AI-generated to explain the trial in plain language. It is not medical advice. Always discuss eligibility with your doctor before enrolling in a clinical trial.
Interested in this trial?
Get notified about updates and connect with the research team.
Interventions
This intervention involves the use of a custom-built artificial intelligence (AI) diagnostic model that integrates multimodal data-including clinical variables, histopathological features, and imaging data-to predict lymph node metastasis in patients with T1-stage gastric cancer. The model provides risk probability scores and classification outputs that assist physicians in diagnostic decision-making. The AI system will be compared with physician performance at different levels of experience (resident, attending, senior) to assess its impact on diagnostic accuracy and clinical decision support.
Locations(1)
View Full Details on ClinicalTrials.gov
For the most up-to-date information, visit the official listing.
NCT07124754